Title :
Using machine learning to understand manufacturing control issues
Author :
Whitehall, Bradley L. ; Fulkerson, Bill ; Hall, James ; Lu, Stephen C -Y
Author_Institution :
Knowledge-based Eng. Syst. Res. Lab., Illinois Univ., Champaign, IL, USA
Abstract :
The authors describe how machine learning can be used to help departmental supervisors to operate a factory as an integrated system. The feasibility of predicting potential problems on the shop floor using symbolic machine learning and neural networks is demonstrated with simulated data of a single department, paint system, and final assembly line. Rules of operation implicit in the simulation model were identified by both methods
Keywords :
learning (artificial intelligence); learning systems; manufacturing computer control; neural nets; machine learning; manufacturing control; neural networks; simulation model; Assembly systems; Knowledge engineering; Machine learning; Manufacturing; Neural networks; Paints; Production facilities; Production systems; Rivers; Systems engineering and theory;
Conference_Titel :
Artificial Intelligence for Applications, 1992., Proceedings of the Eighth Conference on
Conference_Location :
Monterey, CA
Print_ISBN :
0-8186-2690-9
DOI :
10.1109/CAIA.1992.200029
